Abstract. Here we sketch the rudiments of what constitutes a smart city which we define as a city in which ICT is merged with traditional infrastructures, coordinated and integrated using new digital technologies. We first sketch our vision defining seven goals which concern: developing a new understanding of urban problems; effective and feasible ways to coordinate urban technologies; models and methods for using urban data across spatial and temporal scales; developing new technologies for communication and dissemination; developing new forms of urban governance and organisation; defining critical problems relating to cities, transport, and energy; and identifying risk, uncertainty, and hazards in the smart city. To this, we add six research challenges: to relate the infrastructure of smart cities to their operational functioning and planning through management, control and optimisation; to explore the notion of the city as a laboratory for innovation; to provide portfolios of urban simulation which inform future designs; to develop technologies that ensure equity, fairness and realise a better quality of city life; to develop technologies that ensure informed participation and create shared knowledge for democratic city governance; and to ensure greater and more effective mobility and access to opportunities for a

Despite a century of effort, our understanding of how cities evolve is still woefully inadequate. Recent research, however, suggests that cities are complex systems that mainly grow from the bottom up, their size and shape following well-defined scaling laws that result from intense competition for space. An integrated theory of how cities evolve, linking urban economics and transportation behavior to developments in network science, allometric growth, and fractal geometry, is being slowly developed. This science provides new insights into the resource limits facing cities in terms of the meaning of density, compactness, and sprawl, and related questions of sustainability. It has the potential to enrich current approaches to city planning and replace traditional top-down strategies with realistic city plans that benefit all city dwellers.

This is perhaps the most ambitious book written by Mike Batty so far, in which he aims to lay the foundation for what he calls the new science of cities. Ohio-based artist Amy Casey's artwork Twist (amycasepainting.com) is featured prominently on the hard cover of Batty's book. Casey's artwork, according to Batty, captures the essence of complex cities, which contains a mixture of memes and genes, tendons and neurons, machines and organisms, etc. As artist Paul Klee once observed that 'art does not reproduce what we see; rather, it makes us see.' Like Casey's artwork, which has artistically shown us how everything in the real world can be linked together in convoluted ways, Batty's new book has also enabled us to see patterns of urban development in refreshing ways. After a brief preamble, the book is organized in three parts with a total of 14 chapters. The three chapters in Part I cover the foundations and prerequisites for the rest of the book. Chapter 1 is a synoptic overview of all the major concepts for the new science of cities, followed by a more detailed discussion on flows and networks in Chapters 2 and 3, which constitutes the foundation for his new science of cities. The six chapters in Part II are devoted to cover the positive (focusing on 'what is') dimension of the city science, and the five chapters in Part III focus on the normative (focusing on 'what should be') aspect of the new science. In Part II of the book, Batty applies the tools and methods introduced in Part I to examine six aspects of urban growth and development: (1) rank-size and growth clocks (Chapter 4); (2) hierarchies and systems of cities (Chapter 5); (3) space syntax (Chapter 6); (4) complex networks (Chapter 7); (5) fractal growth (Chapter 8); and (6) urban simulation (Chapter 9). The simulation models covered include simple stochastic models, bottom-up evolutionary models, and aggregate land-use transportation models. Part III of the book shifts gears from understanding cities to their design. The central concern of all these five chapters in Part III is how to resolve conflicts or reach consensuses between relevant stakeholders in the design and decision-making process for urban development. Although less technical than the chapters in Part II, the breadth and depth of the five chapters in Part III are equally impressive, ranging from hierarchical design (Chapter 10), Markovian design (Chapter 11) to theories of collective action (Chapter 12) and urban development as exchange and communication (Chapters 13 and 14). The book ends with a brief concluding chapter on the future of the science of cities, with intriguing musings on the prospects of integrating and synthesizing both the positive and normative science of cities. With an active research career spanning over five decades, Batty has made extraordinary contributions to the development of urban modeling by the three books he published earlier (Batty 1976, 2005, Batty and Longley 1994). The current book is a continuation of his lifelong quest to better understand cities an...

Cities can be characterized and modelled through different urban measures. Consistency within these observables is crucial in order to advance towards a science of cities. Bettencourt et al. have proposed that many of these urban measures can be predicted through universal scaling laws. We develop a framework to consistently define cities, using commuting to work and population density thresholds, and construct thousands of realizations of systems of cities with different boundaries for England and Wales. These serve as a laboratory for the scaling analysis of a large set of urban indicators. The analysis shows that population size alone does not provide us enough information to describe or predict the state of a city as previously proposed, indicating that the expected scaling laws are not corroborated. We found that most urban indicators scale linearly with city size, regardless of the definition of the urban boundaries. However, when nonlinear correlations are present, the exponent fluctuates considerably.